Strategies and benchmarks for reducing AI coding assistant token usage and API costs.
Team-scale Claude Code costs multiply individual inefficiencies 8-15x. Here's the playbook: shared context engine, standardized CLAUDE.md, per-developer keys, and the actual ROI math.
Hitting Claude Code rate limits? The root cause is usually high tokens per request, not total usage. Here's the math and the fixes.
Compare manual Claude Code token-saving tactics with automated context engines like vexp, with real numbers on savings, tradeoffs, and setup.
Why Claude Code sessions degrade over time, what’s really filling your context window, and how vexp-style context engineering fixes it.
Most tokens in a typical Claude Code session are exploration overhead and history accumulation — not useful work. Here's the data and what to do about it.
Claude Code feels expensive because context is cumulative — you pay for the full conversation history on every turn. Here's what's burning your budget and how to cut it.
A real-money breakdown of Claude Code API vs Pro vs Max plans, with benchmarked data on how to cut your bill in half without sacrificing output quality.
Use a dependency-graph MCP server (vexp) to feed Claude Code only structurally relevant context and cut token costs by ~58%—no prompt changes required.